High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models

9 April 2022

Papers citing "High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models"

9 / 9 papers shown

Title
The high-dimensional asymptotics of first order methods with random data Michael Celentano Chen Cheng Andrea Montanari AI4CE 17 37 0 14 Dec 2021
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat Francis R. Bach MLT 61 336 0 11 Feb 2020
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 68 332 0 13 Jun 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 64 500 0 31 May 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 117 769 0 12 Nov 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei Jason D. Lee Qiang Liu Tengyu Ma 114 245 0 12 Oct 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 125 652 0 03 Aug 2018
Convergence of Gradient Descent on Separable Data Mor Shpigel Nacson Jason D. Lee Suriya Gunasekar Pedro H. P. Savarese Nathan Srebro Daniel Soudry 58 167 0 05 Mar 2018
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning Siyuan Ma Raef Bassily M. Belkin 48 289 0 18 Dec 2017